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Python代码from mpl_toolkits.mplot3d import Axes3Dimport numpy as npimport matplotlib.pyplot as plt# ============= warmUpExercise ====================def warmUpExercise(D): # Part 1 print(n...

Python代码import numpy as npimport matplotlib.pyplot as pltdef featureNormalize(X): X_norm = X mu = np.zeros((1, X.shape[1])) sigma = np.zeros((1, X.shape[1])) mu = np.mean(X, axi...

代码：# Machine Learning Online Class - Exercise 2: Logistic Regressionimport numpy as npimport matplotlib.pyplot as pltimport scipy.optimize as opdef sigmoid(x): return 1 / (1 + np.exp(-x))...

代码import numpy as np import matplotlib.pyplot as plt import scipy.optimize as op def plotData(X, y): index0 = list() index1 = list() j = 0 for i in y: if i == 0: ...

代码import numpy as npfrom scipy.io import loadmatimport matplotlib.pyplot as pltimport scipy.optimize as opimport mathfrom scipy import optimizedef displayData(X, *example_width): if exa...

代码import numpy as npimport matplotlib.pyplot as pltfrom scipy.io import loadmatimport mathdef displayData(X, *example_width): if example_width == (): example_width = round(np.sqrt...

代码import numpy as npimport matplotlib.pyplot as pltfrom scipy.io import loadmatimport mathimport scipy.optimize as opdef displayData(X, *example_width): if example_width == (): exa...